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Remote Computer Engineering Jobs in California (NOW HIRING)

Computer Vision Engineer

San Francisco, CA ยท On-site +1

$141K - $184K/yr

  • Medical

  • Retirement

  • PTO

We are a team of more than 175 people working in a hybrid-remote environment across North America ... Document experiments, engineering decisions, and best practices. * Take on a variety of technical ...

Lead Engineer

San Mateo, CA ยท On-site +1

$116K - $153K/yr

MS in Computer Science, Computer Engineering or a related field * Experience working with remote teams across multiple locations * Experience with Kubernetes and Docker * CI tools (Jenkins, Circle CI ...

Lead Engineer

San Mateo, CA ยท Remote

$116K - $153K/yr

MS in Computer Science, Computer Engineering or a related field * Experience working with remote teams across multiple locations * Experience with Kubernetes and Docker * CI tools (Jenkins, Circle CI ...

  • Medical

  • Dental

  • Vision

  • PTO

Collaborate with our local and remote developer team * Help document our app * Perform routine ... Previous experience in software development, computer engineering, or other related fields

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Showing results 1-20

Remote Computer Engineering information

See California salary details

$47.9K

$119.9K

$135.7K

How much do remote computer engineering jobs pay per year?

As of Aug 14, 2026, the average yearly pay for remote computer engineering in California is $119,924.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $129,800.00 per year, depending on experience, location, and employer.

How do remote computer engineers typically collaborate with team members across different time zones?

Remote computer engineers often work with colleagues located in various parts of the world, which requires effective communication and collaboration tools. Teams usually rely on project management platforms, version control systems, and regular video meetings to stay aligned. Clear documentation, asynchronous communication, and flexible schedules help ensure that everyone can contribute efficiently, even when working hours don't fully overlap. Adapting to this environment can be challenging at first, but it fosters strong communication skills and autonomy.

What are the key skills and qualifications needed to thrive as a remote computer engineer, and why are they important?

To thrive as a Remote Computer Engineer, you need a strong background in computer science, software development, and problem-solving, usually supported by a relevant degree or equivalent experience. Familiarity with programming languages, version control systems like Git, and cloud platforms such as AWS or Azure is typically required, alongside certifications like CompTIA or AWS Certified Solutions Architect. Excellent communication, self-motivation, and time management are essential soft skills for effective remote collaboration and productivity. These skills and qualities are crucial for delivering high-quality technical solutions while working independently in distributed teams.

What is the difference between Remote Computer Engineering vs Remote Software Development?

AspectRemote Computer EngineeringRemote Software Development
Required CredentialsBachelor's in Computer Engineering, certifications like Cisco CCNA or CompTIA Network+Bachelor's in Computer Science or Software Engineering, certifications like Microsoft Certified, AWS Developer
Work EnvironmentDesigning hardware, embedded systems, network infrastructure; often involves labs or on-site hardware testingWriting, testing, and deploying software applications; primarily computer-based work
Employer & Industry UsageTelecommunications, hardware manufacturing, embedded systems companiesTech companies, startups, software firms, IT services

Remote Computer Engineering focuses on hardware design, embedded systems, and network infrastructure, often requiring specialized certifications and hardware labs. In contrast, Remote Software Development centers on coding, testing, and deploying software applications, with a primary emphasis on programming skills and cloud certifications. Both roles are in high demand but serve different technical needs within the tech industry.

What is remote computer engineering?

Remote computer engineering refers to the practice of working as a computer engineer from a location outside of a traditional office, often from home or another remote setting. Remote computer engineers design, develop, test, and maintain computer hardware and software systems, collaborating with teams using digital communication tools. This role requires strong technical skills, self-motivation, and the ability to manage projects independently while staying connected with colleagues virtually. Remote positions are popular in the tech industry due to their flexibility and access to a global talent pool.

What are the most commonly searched types of Computer Engineering jobs in California?

The most popular types of Computer Engineering jobs in California are:

What are popular job titles related to Remote Computer Engineering jobs in California?

For Remote Computer Engineering jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Computer Engineering jobs in California look for?

The top searched job categories for Remote Computer Engineering jobs in California are:

What cities in California are hiring for Remote Computer Engineering jobs?

Cities in California with the most Remote Computer Engineering job openings:

Infographic showing various Remote Computer Engineering job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $119,924 per year, or $57.7 per hour.

Computer Vision Engineer

Pano

San Francisco, CA โ€ข On-site, Remote

$141K - $184K/yr

Full-time

Medical, Retirement, PTO

Posted 10 days ago


Job description

Help us tackle the growing wildfire crisis with the latest advancements in AI and IoT
Who we are
The challenge: Every minute matters in wildfire response. As climate change increases the frequency and intensity of wildfires-with longer fire seasons, drier fuels, and more extreme weather-new ignitions can spread rapidly, putting communities, critical infrastructure, and ecosystems at risk. Today, many wildfires are first reported by members of the public, meaning it can take valuable time to detect a fire, confirm its location and size, and mobilize responders. Fire agencies need faster, more reliable ways to detect, verify, and pinpoint new ignitions so they can respond quickly and prevent small fires from becoming catastrophic events.
About Pano AI: Pano AI is the leader in AI-powered wildfire detection and intelligence, helping fire professionals detect, respond to, and contain wildfires faster and more safely. Our platform combines advanced hardware, software, artificial intelligence, satellite imagery, and other data sources to provide real-time situational awareness and actionable intelligence. Using a network of ultra-high-definition, 360-degree cameras positioned across high vantage points, Pano AI delivers a real-time view of wildfire activity, enabling faster, more informed decision-making when every second counts.
We are a team of more than 175 people working in a hybrid-remote environment across North America and Australia, with headquarters in San Francisco. Our customers include government agencies, utilities, insurers, and private landowners who rely on Pano AI to help protect people, property, and natural landscapes. Pano AI currently serves customers across the United States, Australia, and Canada, monitoring more than 50 million acres worldwide.
Our work has been recognized by Fast Company as one of the Top 10 Most Innovative AI Companies in 2023 and one of the World's Most Innovative Companies in 2026, ranking #1 in Sustainability. We have also been named to TIME's list of the 100 Most Influential Companies of 2025 and recognized by MIT Technology Review as one of the top climate technology companies to watch.
Backed by $89 million in funding from leading investors including Giant Ventures, Liberty Mutual Ventures, Tokio Marine Future Fund, Congruent Ventures, Initialized Capital, Salesforce Ventures, and T-Mobile Ventures, we're building technology that helps communities around the world become more resilient to wildfire. Learn more at www.pano.ai.
The Role
We are looking for a motivated Computer Vision Engineer to help build the next generation of cloud/edge-based vision systems for wildfire detection and environmental monitoring.
In this role, you will work alongside experienced AI researchers and engineers to develop, evaluate, optimize, and deploy computer vision models on both cloud and edge devices. You will gain hands-on experience across modern computer vision, edge AI, embedded systems, and real-world AI deployment.
Beyond wildfire detection, you will contribute to a variety of computer vision projects, including vegetation detection, asset recognition, instance segmentation, scene understanding, and spatial reasoning. We value curiosity, adaptability, and a willingness to learn new technologies and tackle diverse technical challenges as our products evolve.
This is an excellent opportunity for an engineer who enjoys learning across the entire AI stack and wants to grow into a senior technical contributor.
What you'll do
  • Assist in developing computer vision models for:
    • Wildfire smoke detection
    • Vegetation detection and classification
    • Asset detection and recognition
    • Instance and semantic segmentation
    • Scene understanding and spatial reasoning
  • Help implement and maintain machine learning and computer vision pipelines.
  • Assist with deploying and optimizing AI models on NVIDIA Jetson and other edge platforms.
  • Support model optimization efforts, including TensorRT conversion, quantization, and inference acceleration.
  • Build tools for data processing, visualization, benchmarking, evaluation, and monitoring.
  • Conduct experiments, analyze model performance, and present findings to the team.
  • Debug inference, deployment, networking, and hardware integration issues.
  • Contribute to continuous learning, model evaluation, and data quality improvement workflows.
  • Collaborate closely with AI researchers, software engineers, hardware engineers, and product teams.
  • Document experiments, engineering decisions, and best practices.
  • Take on a variety of technical challenges as needed and continuously expand your skills across computer vision and cloud/edge AI.

What you'll bring
Required
  • BS or MS in Computer Science, Electrical Engineering, Robotics, or a related field.
  • 1-3 years of experience (including internships or research) in software engineering, machine learning, or computer vision.
  • Experience with Python and deep learning frameworks such as PyTorch.
  • Understanding of machine learning fundamentals and modern computer vision techniques.
  • Familiarity with Linux development environments.
  • Strong problem-solving skills, curiosity, and a desire to learn.
  • Excellent communication and teamwork skills.

Preferred
  • Experience with NVIDIA Jetson, CUDA, TensorRT, ONNX, or embedded AI platforms.
  • Experience with OpenCV.
  • Experience with one or more of the following:
    • Object detection
    • Instance or semantic segmentation
    • Image classification
    • Multi-object tracking
    • Video understanding
  • Familiarity with vision foundation models such as SAM, Grounding DINO, or DINO is a plus.
  • Experience with cloud platforms, MLOps, or CI/CD workflows.
  • Interest in deploying AI systems in real-world environments, particularly outdoor vision systems.

Final compensation for regular full-time employees is determined by a variety of factors, including job-related qualifications, education, experience, skills, knowledge, and geographic location. In addition to base salary, regular full-time roles are eligible for equity. Benefits are tailored to local market standards and statutory requirements in the employee's country of employment, and may include health coverage, retirement or pension contributions, and paid time off. Specific benefit details will be shared during the interview process.